Cira PERNA | STATISTICAL INFERENCE
Cira PERNA STATISTICAL INFERENCE
cod. 0212800009
STATISTICAL INFERENCE
| 0212800009 | |
| DEPARTMENT OF ECONOMICS AND STATISTICS | |
| EQF6 | |
| STATISTICS FOR BIG DATA | |
| 2022/2023 |
| OBBLIGATORIO | |
| YEAR OF COURSE 2 | |
| YEAR OF DIDACTIC SYSTEM 2018 | |
| AUTUMN SEMESTER |
| SSD | CFU | HOURS | ACTIVITY | |
|---|---|---|---|---|
| SECS-S/01 | 10 | 60 | LESSONS |
| Objectives | |
|---|---|
| EDUCATIONAL OBJECTIVES: THE COURSE AIMS TO ACQUIRE THE FUNDAMENTALS OF PROBABILITY THEORY AS WELL AS THE PRINCIPLES OF INFERENCE STATISTICS. KNOWLEDGE AND UNDERSTANDING. DURING THE COURSE, THE GENERAL CONCEPTS AND METHODS OF STATISTICAL INFERENCE WILL BE PRESENTED, WITH EMPHASIS ON REGARD TO PROBLEMS OF POINT AND INTERVAL ESTIMATION AND HYPOTHESIS TESTING, USING THE APPROACH BASED ON LIKELIHOOD. WITH THIS IN MIND, THE TOOLS FOR CALCULATING THE PROBABILITY NEEDED. THE STATISTICAL TOOLS INTRODUCED IN THE COURSE WILL BE PRESENTED HIGHLIGHTING THEIR POSSIBLE USE IN EMPIRICAL CONTEXTS. DURING THE TEACHING, CASE STUDIES ARE PROPOSED THROUGH WHICH STUDENTS CAN APPRECIATE THE BENEFITS OF USING INFERENTIAL STATISTICAL TOOLS TO REFINE DECISION-MAKING SKILLS. APPLYING KNOWLEDGE AND UNDERSTANDING. THROUGHOUT THE COURSE, THE STUDENT IS GIVEN EVIDENCE OF HOW TO APPROPRIATELY SELECT AND APPLY THE TOOLS ACQUIRED AS WELL AS HOW TO INTERPRET AND COMMENT ON THE RESULTS OF THE ANALYSES PERFORMED. THE KNOWLEDGE ACQUIRED WILL ENABLE THE STUDENT TO BE ABLE TO IDENTIFY THE PROBABILISTIC AND INFERENTIAL TOOLS BEST SUITED FOR THE ANALYSIS OF A PROBLEM, TO FORMULATE A STATISTICAL PROBLEM FROM A REAL PROBLEM, TO ESTIMATE PARAMETERS BY THE MAXIMUM LIKELIHOOD METHOD, AND TO ASSESS THEIR SIGNIFICANCE BY APPROPRIATE STATISTICAL TESTS. |
| Prerequisites | |
|---|---|
| ANALISI E VISUALIZZAZIONE DEI DATI STATISTICA SPERIMENTALE E APPLICATA |
| Contents | |
|---|---|
| INTRODUCTION TO PROBABILITY. DISCRETE AND CONTINUOUS RANDOM VARIABLES. PRINCIPLES AND METHODS OF STATISTICAL INFERENCE. RANDOM SAMPLES. SAMPLING DISTRIBUTIONS. ASYMPTOTIC SAMPLING DISTRIBUTIONS. SIMULATION TECHNIQUES FOR THE DETERMINATION OF A SAMPLING DISTRIBUTION. INTRODUCTION TO RESAMPLING METHODS. THE JACKNIFE METHOD. THE BOOTSTAP. EXAMPLES AND APPLICATIONS OF BOOTSTRAP. THE LIKELIHOOD FUNCTION. THEORY OF ESTIMATORS. ESTIMATORS AND ESTIMATES. SUFFICIENCY OF AN ESTIMATOR. FINITE PROPERTIES OF AN ESTIMATOR. ASYMPTOTIC PROPERTIES OF AN ESTIMATOR. GENERAL PRINCIPLES FOR ESTIMATING A PARAMETER. STATISTICAL VALIDITY OF AN ESTIMATOR. METHODS OF BUILDING AN ESTIMATOR. THE METHOD OF MOMENTS AND ITS GENERALIZATIONS. INTRODUCTION TO THE LEAST SQUARES METHOD. MAXIMUM LIKELIHOOD METHOD: PRINCIPLES AND APPLICATIONS. MAXIMUM LIKELIHOOD METHODS: PROPERTIES AND THEOREMS. CONFIDENCE INTERVALS. THE BOOTSTRAP METHOD FOR DETERMINING CONFIDENCE INTERVALS. INTRODUCTION TO HYPOTHESIS TESTING. LOGIC AND CHARACTERISTICS OF THE TEST. PROBABILISTIC STRUCTURE OF THE TEST. LIKELIHOOD RATIO. ASYMPTOTIC STATISTICAL TESTS. TEST ON THE PARAMETERS OF A NORMAL DISTRIBUTION. |
| Teaching Methods | |
|---|---|
| LECTURES |
| Verification of learning | |
|---|---|
| THE EVALUATION OF THE PROFIT IS MADE ON THE BASIS OF A WRITTEN TEST AND AN ORAL TEST. THE WRITTEN TEST IS AIMED TO ASSESS THE STUDENT'S ABILITY TO USE THE STATISTICAL TECHNIQUES ACQUIRED DURING THE COURSE. THE TRACK OF THE WRITTEN TEST INCLUDES THREE EXECISES WORTH 1-10 POINTS EACH, FOR A TOTAL SCORE OF 30. THE ORAL TEST, OF ABOUT 20 MINUTES, IS INTENDED TO EVALUATING THE ARGUMENTATION CAPACITY, THE ACCURACY OF LANGUAGE AND THE ABILITY TO MAKE CRITICAL USE OF THE ACQUIRED STATISTICAL TOOLS. THE FINAL SCORE WILL TAKE INTO ACCOUNT BOTH THE WRITTEN AND ORAL EVALUATIONS. |
| Texts | |
|---|---|
| D. PICCOLO, STATISTICA,1998, IL MULINO (III EDIZIONE) |
| More Information | |
|---|---|
| ADDITIONAL MATERIALS WILL BE PROVIDED DURING THE COURSE |
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